Towards Optimal Solar Tracking: A Dynamic Programming Approach


  • Athanasios Aris Panagopoulos University of Southampton, UK
  • Georgios Chalkiadakis Technical University of Crete
  • Nicholas Jennings University of Southampton



Solar tracking, Energy Efficiency, Smart Grid, MDP, Dynamic programming, Policy Iteration, Alternating


The power output of photovoltaic systems (PVS) increases with the use of effective and efficient solar tracking techniques. However, current techniques suffer from several drawbacks in their tracking policy: (i) they usually do not consider the forecasted or prevailing weather conditions; even when they do, they (ii) rely on complex closed-loop controllers and sophisticated instruments; and (iii) typically, they do not take the energy consumption of the trackers into account. In this paper, we propose a policy iteration method (along with specialized variants), which is able to calculate near-optimal trajectories for effective and efficient day-ahead solar tracking, based on weather forecasts coming from on-line providers. To account for the energy needs of the tracking system, the technique employs a novel and generic consumption model. Our simulations show that the proposed methods can increase the power output of a PVS considerably, when compared to standard solar tracking techniques.




How to Cite

Panagopoulos, A. A., Chalkiadakis, G., & Jennings, N. (2015). Towards Optimal Solar Tracking: A Dynamic Programming Approach. Proceedings of the AAAI Conference on Artificial Intelligence, 29(1).



Computational Sustainability and Artificial Intelligence